Toward principles for the design of ontologies used for knowledge sharing
International Journal of Human-Computer Studies - Special issue: the role of formal ontology in the information technology
Knowledge engineering: principles and methods
Data & Knowledge Engineering - Special jubilee issue: DKE 25
Reconciling schemas of disparate data sources: a machine-learning approach
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Semantic integration: a survey of ontology-based approaches
ACM SIGMOD Record
Using Element Clustering to Increase the Efficiency of XML Schema Matching
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
Putting context into schema matching
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
A unified approach for schema matching, coreference and canonicalization
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Developing a semantic-enable information retrieval mechanism
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A novel clustering-based approach to schema matching
ADVIS'06 Proceedings of the 4th international conference on Advances in Information Systems
Discussions on semantic-based in decision support systems
ECC'11 Proceedings of the 5th European conference on European computing conference
Hi-index | 12.05 |
In many domains today there are very limited explicit ontologies established for implementing information systems. Traditional ontology-driven semantic integration approaches cannot be directly applied in integrating these information systems. Usually, the information systems have schemas, a type of formal information model, for their information repositories which to some extent imply the semantics of the information. Each schema actually reflects a specific view of the domain conceptualization. This paper investigates the theoretical foundation of ontologies and extends the traditional ontology concept to the ontological view concept. It proposes to use ontological views to address the challenge of semantic integration. The proposed approach adopts the schemas to create local ontological views, uses data instances of the information systems to discover semantic relationships between the concepts within the ontological views, and builds a domain ontological view based on the discovered equivalence mappings. It applies the hierarchical clustering technique on the data instances and, in the further analysis, uses the clusters to reduce the cost of processing a large amount of data. The matching of concept properties is based on the probability distribution of the data instances. The experimental results have demonstrated the effectiveness of this approach.